Parkinsonism is a Phenotypical Signature of Amyloidopathy in Patients with Gait Disorders

Abstract

Background:

Central neurological gait abnormalities (CNGA) are frequently associated with parkinsonism in older adults. However, the neuropathological substrates and the clinical impact of parkinsonism have been not described in CNGA.

Objective:

This cross-sectional study aims to compare the CSF total tau, Aβ_1-42, and phosphorylated tau levels in non-Parkinson’s disease (PD) patients with CNGA with and without parkinsonism and to study the clinical impact of parkinsonism on gait and cognition.

Methods:

CSF biomarkers were measured by ELISA in 49 non-PD patients with CNGA (77.7±6.6 years; 32.7% women). Gait was quantified with an optoelectronic system and cognition with a comprehensive neuropsychological assessment. Parkinsonism was defined by presence of bradykinesia and at least one of the following signs among muscular rigidity, rest tremor, or postural instability.

Results:

Parkinsonism was identified in 14 CNGA patients (28.6% ). CSF Aβ_1-42 level was decreased in CNGA patients with parkinsonism (β: – 189.4; 95% CI [– 352.3; – 26.6]; p = 0.024) even after adjusting for age, gender, comorbidities, and total white matter burden; while CSF total tau and phosphorylated tau levels were similar between CNGA patients with and without parkinsonism. CNGA patients with parkinsonism presented decreased attentional and executive performances but similar gait parameters than those without parkinsonism.

Conclusion:

Parkinsonism represents a phenotype related with amyloidopathy—decreased CSF Aβ_1-42 level—in non-PD patients with CNGA. This phenotype is clinically associated with impaired cognition, but similar quantitative gait parameters in comparison to CNGA patients without parkinsonism.

Keywords

Amyloidopathy biomarkers dementia gait disorders parkinsonism

INTRODUCTION

Gait disorders are common in older adults with neurological conditions, with a prevalence reaching 93% [1] and are associated with bad clinical outcomes, such as dementia [2, 3], institutionalization [4], and mortality [4]. Neurological gait abnormalities can be divided into peripheral and central origins [2, 5] secondary to normal pressure hydrocephalus, vascular and/or neurodegenerative pathologies [6]. In contrast to subjects with neurological gait abnormalities from a peripheral origin, older patients with central neurological gait abnormalities (CNGA) are functionally unable to increase their brain perfusion while walking in challenging conditions [5]. Around 30% of patients with CNGA also have parkinsonism [7] and slow gait has been identified as a predictor of persistent parkinsonism in aging, driven by an underlying neurodegenerative mechanism [8]. However, in patients with CNGA, the clinical impact of parkinsonism on gait parameters and cognitive functions is unknown. Moreover, its neuropathological substrates remain poorly understood, possibly related to white matter disease [9 –11], cholinergic denervation [12 –14], or the α-synuclein pathway [15]. To date, only two studies have revealed that decreased cerebrospinal fluid (CSF) amyloid-β (Aβ)_1-42 levels were associated with gait disturbances in Parkinson’s disease (PD) [16, 17] and one study demonstrated that a low CSF Aβ_1-42 level was associated with dopa-resistant gait disturbances in PD [18]. Similarly, in aging studies, amyloid burden has been associated with poor gait [19 –22].

Therefore, we propose to compare simultaneous measurements of CSF Aβ_1-42, total tau (t-tau), and tau phosphorylated at threonine 181 (phospho-tau) as well as both neuropsychological and quantitative gait parameters in non-PD patients presenting with CNGA, contrasting those with and those without parkinsonism. As CSF Aβ_1-42 levels have been associated with gait disturbances in PD and aging [16 , 19–22], we hypothesized that CNGA non-PD patients with parkinsonism may present lower CSF Aβ_1-42 level compared to those without parkinsonism. Establishing the clinical and biochemical changes related to parkinsonism in non-PD patients with CNGA could improve our understanding of the pathogenesis of this phenotype in order to improve the clinical management of these patients.

MATERIAL AND METHODS

2.1 Participants

A total of 51 consecutive non-PD patients assessed in the Department of Neurology of the Geneva University Hospitals between October 2012 and July 2016 for the investigation of gait disorders (more specifically CNGA), and who agreed to perform an analysis of CSF biomarkers were retrospectively included in this study. Following routine clinical gait assessment, CNGA were clinically defined by a frontal, parkinsonian, hemiparetic, unsteady, or spastic subtype, as previously described [2]. Gait subtypes were not mutually exclusive. Inclusion criteria for this analysis were all non-PD patients older than 60 with 1) a complete neurological examination and a specific assessment of parkinsonism, 2) a comprehensive neuropsychological assessment, 3) a brain imaging (CT or MRI), 4) a measurement of CSF Aβ_1-42, t-tau, and phospho-tau, 4) an ability to walk 10 meters without assistance, and 6) a spatiotemporal gait analysis. Exclusion criteria were 1) presence of an acute medical illness in the past three months, 2) presence of a non-neurological (i.e., orthopedic or rheumatologic) condition or a peripheral neurological condition interfering with gait, 3) presence of clinically significant visual, peripheral or vestibular deficits, 4) use of antipsychotic medications, and 5) a diagnosis of idiopathic PD; PD was excluded based on clinical presentation, especially the presence of red flag symptoms for idiopathic PD: all patients with parkinsonism displayed with at least two red flag symptoms (i.e., recurrent falls>1/year because of impaired balance; and bilateral symmetric parkinsonism) [23]; however, we did not exclude idiopathic PD based on neuropathological examination, or on other clinical tests, such as the response to dopaminergic therapy. No other a priori neurological diagnosis or specific patterns of brain atrophy were excluded; inclusion was only based on gait phenotype. A total of 49 non-PD patients (2 were excluded due to antipsychotic medications) with CNGA were included in the study (77.7±6.6 years; 32.7% women). Among the included patients, the diagnoses were normal pressure hydrocephalus in 27 patients, mixed dementia in 9 patients, vascular dementia in 5 patients, Alzheimer’s disease (AD) in 3 patients, dementia with Lewy bodies in 2 patients, progressive supranuclear palsy in 2 patients, and alcohol-related dementia in 1 patient. Presence of parkinsonism was assessed by the same board-certified neurologist (GA) and followed the definition of the United Kingdom Parkinson’s disease society brain bank clinical diagnostic criteria (step one: presence of bradykinesia and at least one of the following sign: muscular rigidity, rest tremor or postural instability) [24]. This study protocol was approved by the ethical committee of Geneva University Hospitals.

2.2 CSF sample collection and analysis of CSF biomarkers

CSF sample collection was performed by an experimented neurologist at the same time of the day (between 10 and 12 am) to avoid potential diurnal variations [25]. CSF proteins (Aβ_1-42, t-tau, and phospho-tau) were analyzed on 10 ml CSF after patient’s approval, following the international recommendations of the AD biomarkers standardization initiative [26]. Briefly, CSF samples were collected into 10 ml polypropylene tubes (Sarstedt PP tubes), centrifuged at 4°C for 10 min at 2000 g within 4 h after lumbar puncture to remove cells, aliquoted into 0.5 -mL polypropylene tubes (Sarstedt PP tubes), and stored at – 80°C until analysis. Aβ_1-42, t-tau, and phospho-tau were measured in duplicate using double-sandwich enzyme-linked immunosorbent assay (ELISA) methods (INNOTEST^®, Fujirebio, Gent, Belgium) according to the manufacturer’s instructions.

2.3 Neuropsychological assessment

A standardized neuropsychological assessment was conducted by the same neuropsychologist (ML) to evaluate: executive functions (Color Trails test, Stroop test, phonemic and categorical verbal fluencies), attention (Wechsler Adult Intelligence Scale– III symbol digit test and digit span; Wechsler Memory Scale– III spatial span) and memory (the French version of the Free and Cued Selective Reminding Test [27]). Global cognitive functioning was assessed with the Mini-Mental State Examination (MMSE). Depression and anxiety were assessed by the Hospital Anxiety and Depression Scale [28] and apathy by the Starkstein apathy scale [29].

2.4 Gait evaluation

Spatio-temporal gait parameters were assessed at comfortable walking speed performed under ecological conditions, with patients wearing their own shoes on a distance of 6 meters with an optoelectronic system including 12 cameras (Vicon Motion Systems Ltd, UK). The Timed up and go, which measured in time the distance needed to stand up, walk for 3 m, turn, walk back, and sit down [30], was evaluated at self selected-speed by a physical therapist.

2.5 White matter lesions

White matter lesions were rated using the age-related white matters changes (ARWMC), a valid semi-quantitative scale with moderate to good interrater reliability [31]. The ARWMC was applied to every neuroimaging scanner (43 MRI/6 CT-Scan). Total score (range: 0–30) and subscores (range: 0–6) were computed on the five regions combining the left and right hemispheres: frontal, temporal, parieto-occipital, basal ganglia and infratentorial.

2.6 Covariates

Comorbid illness were rated by the Global health status score (GHS; range 0–9), based on the presence of diabetes, chronic heart failure, arthritis, hypertension, depression, stroke, chronic obstructive pulmonary disease, angina, and myocardial infarction [32]. A vascular risk factor score (range 0–5) was computed on the presence of diabetes, hypertension, hypercholesterolemia, body mass index >30 or smoking; and a cardiovascular risk factor score (range 0–4) on the presence of myocardial infarction, angina, arrhythmia or chronic heart failure [8].

2.7 Statistics

Descriptive statistics of the patients were calculated. Data were represented graphically; model assumptions were tested with skewness and kurtosis. We compared patients with and without parkinsonism based on two-sample t-test, Mann-Whitney U-test or Fischer exact test as appropriate. Univariable and multivariable (adjusted on age, gender, GHS and ARWMC total score) linear regression models were used to compute unstandardized β with 95% confidence intervals to show an association between CSF protein level (dependent variable) and presence of parkinsonism (independent variable). All analyses were conducted using SPSS version 22 (SPSS Inc., Chicago, IL, USA).

RESULTS

Characteristics of CNGA patients are compared between those with and without parkinsonism in Table 1.

Table 1

Clinical characteristics of patient with central neurological gait disorders (n = 49)

	Parkinsonism (n = 14)	No Parkinsonism (n = 35)	p-value^*
Age (y)	76.4±6.2	78.2±6.8	0.308^b
Gender (% female)	35.7	31.4	1.000^c
Disease duration^¶ (mo)	46.3±44.1	28.5±21.6	0.379^b
Comorbidities (GHS, 0–9)	2.21±0.70	1.97±1.04	0.509^b
Vascular Risk Factor^¥ (0–5)	1.79±0.98	1.49±0.95	0.225^b
Cardiovascular Risk Factor^§ (0–4)	0.07±0.26	0.23±0.43	0.204^b
Treatment, (no. of drugs)	4.92±2.84	4.00±2.18	0.394^b
White matter lesions^\|\| (0–30)	8.29±4.05	7.34±4.68	0.577^b
CSF proteins level
Total tau, ng/l	240.2±178.1	250.1±122.6	0.824^a
Phospho-tau, ng/l	39.6±17.3	45.5±18.0	0.304^a
Aβ_1-42, ng/l	568.5±162.4	754.4±271.6	0.012 ^b
Gait parameters
Gait speed, m/s	0.70±0.22	0.75±0.28	0.545^a
Stride time, s	1.20±0.16	1.27±0.24	0.423^b
Stride length, m	0.82±0.23	0.91±0.30	0.312^a
Step width, m	0.10±0.03	0.10±0.05	0.824^a
Stride time variability ^smallint, %	4.22±1.72	4.42±3.33	1.000^a
Timed up and go test, s	22.8±13.5	25.8±23.2	0.808^b

GHS, global health status score. ^*Comparisons are based on two-sample t-test^a, Mann-Whitney U test^b or Fisher exact test^c as appropriate; significant differences (p values <0.05) are in bold. ^¶Defined since beginning of walking difficulties. ^¥Presence of diabetes, hypertension, hypercholesterolemia, body mass index >30 or smoking. ^§Presence of myocardial infarction, angina, arrhythmia, or chronic heart failure. ^smallintCalculated following the formula: standard deviation/mean×100. ^||Rated with the age-related white matter changes.

Overall prevalence of parkinsonism was 28.6% . Both groups showed similar clinical characteristics, including spatio-temporal gait parameters: for the entire group, mean (±SD) gait speed was 0.74±0.27 m/s, and mean TUG 24.95±20.79 s. Patients with parkinsonism presented significantly lower Aβ_1-42 levels in comparison with those without parkinsonism (568.5±162.4 ng/L versus 754.4±271.6 ng/L, p = 0.012). By contrast, both t-tau and phospho-tau levels were similar between the two groups (Fig. 1). The significant decrease of Aβ_1-42 in patients with parkinsonism persists in the multivariable linear regression showing an association between Aβ_1-42 level (dependent variable) and presence of parkinsonism (independent variable) adjusted for age, gender, global cognition (MMSE), and total white matter burden (β: – 191.1; 95% CI [– 353.1; – 29.1]; p = 0.022); this association between low Aβ_1-42 and parkinsonism persisted when adjusting for white matter burden in every brain subregion (including basal ganglia), except for the frontal subregion, where the association was borderline (β: – 150.3; 95% CI [– 326.0;25.5]; p = 0.092). White matter burden was similar in both groups; however, patients with parkinsonism presented a higher white matter burden in the frontal lobe (p = 0.013). The significant decrease of Aβ_1-42 in patients with parkinsonism persists in the logistic regression showing an association between presence of parkinsonism (dependent variable) and Aβ_1-42 level (independent variable) adjusted for total white matter burden (odds ratio: 0.996; 95% CI [0.992;1.000]; p = 0.028) and every brain subregion (including basal ganglia) except for the frontal subregion, where it was borderline (odds ratio: 0.997; 95% CI [0.992;1.001]; p = 0.100). The significant decrease of Aβ_1-42 in patients with parkinsonism persists in the linear regression showing an association between Aβ_1-42 level (dependent variable) and parkinsonism (independent variable) adjusted for age, gender, total white matter burden and neurological diagnoses (β: – 229.3; 95% CI [– 392.9; – 65.8]; p = 0.007).

Fig.1

Box plots comparing CSF level (ng/l) between patients with and without parkinsonism of (A) Aβ_1-42, (B) total tau, and (C) phospho-tau proteins. Box indicates interquartile-range, bars medians, and circles outliers.

Cognitive performances between patients with and without parkinsonism are displayed in Table 2. Global cognition was similar between both groups with a mean (±SD) MMSE for the entire group of 22.8±4.4. Patients with parkinsonism presented decreased performances in executive functions in the dot (p = 0.037), word (p = 0.020), and color (p = 0.002) conditions of the Stroop test, in attention in the Wechsler Adult Intelligence Scale– III symbol digit test (p = 0.021) and in the Wechsler Memory Scale– III backward digit span (p = 0.025), while episodic memory performances were similar between both groups. Anxiety, depression, and apathy symptoms were similar between both groups.

Table 2

Comparisons of cognitive performances between patients with and without parkinsonism (n = 49)

	Parkinsonism (n = 14)	No Parkinsonism (n = 35)	p-value^*
Mini-Mental State Examination (/30)	21.9±4.2	23.1±4.4	0.408^a
Executive functions
Color Trails Test, s
Part 1	155.4±63.7	120.0±71.7	0.135^b
Part 2	272.2±93.8	242.3±94.3	0.556^a
Index^\|\|	1.03±0.51	1.61±0.90	0.149^b
Verbal fluency, n
Semantic	10.9±5.2	11.6±4.8	0.703^a
Phonemic	8.4±6.4	11.1±6.4	0.275^a
Stroop test, s
Dot	28.6±10.2	19.9±5.6	0.037 ^a
Word	43.4±28.9	27.5±9.7	0.020 ^b
Color	74.4±29.9	45.6±24.3	0.002 ^b
Index^‡	2.67±0.75	2.36±0.91	0.157^a
Memory
FCSRT free recall	9.8±6.7	15.5±8.2	0.077^a
FCSRT total recall (free and cued recall)	31.5±12.6	36.8±9.0	0.274^a
Attention
WAIS-III symbol digit modalities test, n	20.6±6.9	30.5±12.4	0.021 ^a
WAIS-III forward digit span, n	4.5±0.9	4.9±1.1	0.164^b
WAIS-III backward digit span, n	3.3±0.9	3.6±1.2	0.025 ^b
WMS-III forward visual span, n	3.5±1.2	4.3±1.1	0.054^b
WMS-III backward visual span, n	3.3±0.9	3.6±1.2	0.407^b
Behaviour
HADS-anxiety (0–21)	8.1±5.8	6.2±3.7	0.198^a
HADS-depression (0–21)	6.5±3.6	5.7±3.2	0.492^a
Starkstein Apathy Scale (0–42)	16.1±4.3	16.2±4.3	0.975^a

FCSRT: Free and Cued Selective Recall Reminding Test; WAIS-III: Wechsler Adult Intelligence Scale-III; WMS-III: Wechsler Memory Scale-III; HADS: Hospital Anxiety and Depression Scale. Values are presented with means (standard deviation). ^*Comparisons are based on two-sample t-test^a or Mann-Whitney U test^b as appropriate; significant differences (p values <0.05) are in bold. Dot, name color of dot; Word, name color print of non-color word; Color, name color print of color word. ^||Color Trails Test index is calculated with the formula: (Part 2-Part 1/Part 1). ^‡Stroop index is calculated with the formula: (Color part/Dot part).

DISCUSSION

While quantitative gait parameters were similar between CNGA patients with and without parkinsonism, those with parkinsonism presented a decreased CSF Aβ_1-42 protein level in comparison to those without parkinsonism, even after adjusting for age, gender, comorbidities (or neurological diagnoses), and white matter burden. CNGA patients with parkinsonism also showed lower cognitive performances in attention and executive domains. In terms of white matter changes, both groups presented a similar total white matter burden, while the group with parkinsonism disclosed increased white matter changes in the frontal lobes. This association between parkinsonism and decreased CSF Aβ_1-42 protein level in CNGA non-PD patients is in line with previous CSF research using the disease-model approach. In PD, patients with the PIGD (postural instability and gait difficulties) phenotype presented a decrease CSF Aβ_1-42 peptide in comparison to those with the tremor dominant phenotype [16, 17]. Amyloid-β peptides promoted alpha-synuclein aggregation in animal models of PD [33]. This association could explain both motor (i.e., parkinsonism) and cognitive disturbances (executive and attentional dysfunctions) in this population of CNGA non-PD patients with parkinsonism. Interestingly, white matter disease affecting specifically the frontal lobes may unsurprisingly contribute to that particular cognitive profile.

Both groups presented similar gait performances (i.e., quantitative gait parameters and Timed up and go test), while they differed in term of executive and attentional performances. This dichotomy between relatively preserved gait parameters and impaired attentional/executive domains in patients with parkinsonism in comparison to those without parkinsonism does not reflect the largely accepted model of attention and executive function on gait control in normal [34] and pathological aging [35]. These findings suggest that CNGA patients with parkinsonism presented neurodegenerative mechanisms related to the amyloid pathway that targets critical brain regions that are not related to gait control, but to cognition. It is also well known that gait parameters are less affected in AD or pre-AD, such as mild cognitive impairment, than other neurodegenerative conditions [36].

This phenotypical approach, instead of a disease-related approach, strongly suggests that parkinsonism represents a clinical marker of amyloidopathy in patients with CNGA. The prevalence of parkinsonism (28.6% ) in our population of patients with CNGA was similar than those previously reported (around 30% ) [7]. A similar phenotypical approach showed that older adults with parkinsonian signs presented a decline in executive functions and decreased plasma levels of Aβ_1-42 protein [37], corroborating that parkinsonian signs, especially axial signs, predicted incident AD [38, 39]. The involvement of white matter disease in older adults with parkinsonian signs, especially with gait disorders, has also been demonstrated [11]. However, AD neuropathology also contributes to parkinsonism, especially when located in the substantia nigra [40]. Interestingly, neurofibrillary tangles in the substantia nigra have been associated with parkinsonian signs in older adults without PD [41]. Although the phenotypical presentation of CNGA is atypical for AD, this association between low level of CSF Aβ_1-42 protein and parkinsonism may suggest the presence of a comorbid AD pathology in this subgroup of patients. Parkinsonism and central neurological gait abnormalities in older adults with earlier signs of cognitive decline are often found in patients with Lewy body disease, more often than in patients with AD [42, 43]. A comorbid AD pathology is found in over 75% cases of autopsy-confirmed Lewy body disorders [44]; this suggests that the subgroup of patients with parkinsonism and low level of CSF Aβ_1-42 peptide may also have a comorbid Lewy body disease. The increased prevalence of mixed neuropathology in aging [45 –47] encourages clinicians to adopt a phenotypical rather than a disease approach to disentangle the pathophysiological mechanism underlying parkinsonism in patients with CNGA, as previously suggested [48].

Including CSF biomarkers, quantitative gait parameters and a detailed cognitive assessment in such a large cohort of non-PD patients with CNGA represent the main strengths of this study. However, the lack of a validated quantitative scale to assess parkinsonism in older adults, as the UPDRS for PD patients, prevents us to quantify the severity of parkinsonism in our patients. Furthermore, the retrospective design of this study limited our descriptive approach of parkinsonian signs and prevented a comparison of the impact of axial versus peripheral parkinsonian signs. Future investigations in a larger sample should assess the association between CSF biomarkers and gait variables in CNGA with and without parkinsonism, using a standardized MRI scanning protocol to evaluate the contribution of brain atrophy.

In conclusion, our findings provide new insights in the neurobiology of CNGA non-PD patients, suggesting that the presence of parkinsonism is associated with an underlying amyloid pathology. This phenotypical approach, reflecting clinical practice, shows that CNGA patients with parkinsonism display preserved gait parameters, but impaired attentional and executive performances. Future studies should include detailed and quantified measures of parkinsonism, including axial and peripheral signs, as well as in vivo measurements of amyloid plaques (i.e., amyloid-PET) in order to better understand this clinical phenotype.

Footnotes

ACKNOWLEDGMENTS

This study was funded by the Geneva University Hospitals (PRD 11-I-3 and PRD 12-2013-I) and the Swiss National Science Foundation (320030_173153).

Authors’ disclosures available online ().

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